Stars
ML models + benchmark for tabular data classification and regression
Travel planning Streamlit web-app based on OpenAI API
⚡️ GenBI (Generative BI) queries any database in natural language, generates accurate SQL (Text-to-SQL), charts (Text-to-Chart), and AI-powered insights in seconds.
skfeaturellm is a Python library that brings the power of Large Language Models (LLMs) to feature engineering for tabular data, wrapped in a familiar scikit-learn–style API.
Examples of PyMC models, including a library of Jupyter notebooks.
A secure and easy-to-use tool for managing sensitive data with built-in encryption, decryption, and key management. Protect your secrets during development, testing, and deployment with CLI command…
A library to find and visualise the most interesting slices in multidimensional data
Improving XGBoost survival analysis with embeddings and debiased estimators
Self-contained examples for Amadeus REST APIs
Meta-Transformer for Unified Multimodal Learning
Streamlit Component for rendering Folium maps
👀🛡️ Code for the paper “Carefully Blending Adversarial Training and Purification Improves Adversarial Robustness” by Emanuele Ballarin, Alessio Ansuini and Luca Bortolussi (2024)
Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.
Code and documentation to train Stanford's Alpaca models, and generate the data.
A collection of libraries to optimise AI model performances
OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
Neural Networks: Zero to Hero
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Topic modeling helpers using managed language models from Cohere. Name text clusters using large GPT models.
Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Github repo with tutorials to fine tune transformers for diff NLP tasks
Notebooks using the Hugging Face libraries 🤗
[WWW 2022] Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations